Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Genetic prediction of medication use patterns in cardiometabolic disease

By performing a large-scale biobank-based genome-wide association study, we identified a strong link between the underlying risk of cardiometabolic disease and patterns of lifelong medication use in hyperlipidemia, hypertension and type 2 diabetes. We discover hundreds of genetic predictors of medication use behavior and show medication-use-enhanced applications for polygenic prediction in cardiometabolic diseases.

This is a preview of subscription content, access via your institution

Access options

Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Relationship between drug purchases and underling cardiometabolic risk factors.


  1. James, S. L. et al. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 392, 1789–1858 (2018). A review article that presents global burden of 354 disease including cardiovascular diseases.

    Article  Google Scholar 

  2. Marenberg, M. E., Risch, N., Berkman, L. F., Floderus, B. & de Faire, U. Genetic susceptibility to death from coronary heart disease in a study of twins. New Engl. J. Med. 330, 1041–1046 (1994). This paper reports heritability estimates for coronary heart disease.

    Article  CAS  Google Scholar 

  3. SEARCH Collaborative Group. SLCO1B1 variants and statin-induced myopathy—a genomewide study. New Engl. J. Med. 359, 789–799 (2008). A review article that presents evidence for adverse reactions to statin use for individuals carrying risk variants in the SLCO1B1 gene.

    Article  Google Scholar 

Download references

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This is a summary of: Kiiskinen, T. et al. Genetic predictors of lifelong medication use patterns in cardiometabolic diseases. Nat. Med. (2023).

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Genetic prediction of medication use patterns in cardiometabolic disease. Nat Med 29, 43–44 (2023).

Download citation

  • Published:

  • Issue Date:

  • DOI:


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing